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Artificial Intelligence (AI) is revolutionizing the field of Magnetic Resonance Imaging (MRI) by enabling faster, more accurate, and cost-effective image reconstruction. This project explores
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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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experience in at least one of the following would be highly regarded: (i) the theory and simulation of scattering, diffraction and imaging with high energy electrons or X-rays; (ii) solving inverse scattering
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Fellow. This role offers the chance to be at the forefront of innovation in chemical biology, with a focus on developing cutting-edge tools for molecular sensing and imaging. Under the guidance of Dr
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prototype integration to translate sensor outputs into clinically relevant protein biomarker data. The role will involve laboratory-based experimentation, data analysis, and active contribution to scholarly
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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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, in various formats including images, texts and numeric values. The study of these unstructured data in the pathology laboratory information system (LIS), together with the information from
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displacement and the length of such deformations (or displacements). As later steps, we will then look at time series data (or movies of images) and also at out-of-plane 3-dimensional deformations. This will
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malfunction and is associated with high morbidity and mortality. Current imaging techniques of fibrosis are indirect and possess substantial limitations, hence the medical need for accurate and sensitive